CN110381267B - Method for realizing large-format multilayer real-time editing based on intra-frame segmentation clustering - Google Patents
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Abstract
The invention discloses a method for realizing large-format multilayer real-time editing based on intra-frame segmentation clustering, which relates to the technical field of video editing and comprises the following steps: s1: forming an InfiniBand network cluster by using a plurality of machines, and configuring an InfiniBand network card for each machine; s2: setting each machine to have the same timeline information, so that the timeline data structures of all the machines are synchronous; s3: decoding and editing an input video file to obtain decoded video data, then dividing the decoded video data into a plurality of regions according to space, rendering the decoded video data of each region in parallel, and finally obtaining a rendering result of each region; s4: the rendering results of all the areas are stitched and spliced into a complete picture to finish editing, a plurality of machines are adopted to form a cluster, the calculation tasks with heavy multilayer large-format editing are split into different machines to be processed in an intra-frame splitting mode, and free and smooth multilayer large-format real-time editing is realized.
Description
Technical Field
The invention relates to the technical field of video editing, in particular to a method for realizing large-format multilayer real-time editing based on intra-frame segmentation clustering.
Background
Large format video has a huge amount of data, and in 8K for example, a non-linear editing system needs to edit a layer of 8K4:2: 210 bit50P video, which needs to process more than 50Gbit data per second, and the processing includes very complicated stun such as decoding and rendering. The hardware capability of the current single-machine nonlinear editing system is completely insufficient for editing 8K videos, and the method is embodied in the following aspects:
1. the decoding capability of a CPU is insufficient, when an existing Intel high-end two-way to strong gold medal processor decodes 8K videos, only one layer can be in real time, two layers cannot be in real time, and the real time of multiple layers is not the same;
2. the GPU rendering capability is insufficient, and the 8K format rendering is difficult to achieve real time under the condition of complex special effects;
3. the data uplink and downlink speed of the GPU is insufficient, the current GPU is inserted into a slot of PCIE3.0 × 16, limited by PCIE bandwidth, only one uplink path of 8K data and one downlink path of 8K data can be barely simultaneously, and uplink and downlink of multiple layers of 8K data cannot be supported;
at present, non-editing products on the market are in a single machine form, and the hardware capability of a single machine nonlinear editing system cannot meet the editing requirement of a user on an 8K video, so that the development of an editing method capable of realizing unlimited breadth, unlimited layer number and unlimited frame rate is a main task at present.
Disclosure of Invention
The invention aims to: the invention provides a method for realizing large-breadth multilayer real-time editing based on intra-frame segmentation clustering, which aims to solve the problems that non-editing products on the market are in a single machine form at present, and the hardware capability of a single machine nonlinear editing system cannot meet the editing requirement of a user on an 8K video.
The invention specifically adopts the following technical scheme for realizing the purpose:
the method for realizing large-format multilayer real-time editing based on intra-frame segmentation clustering comprises the following steps:
s1: forming an InfiniBand network cluster by using a plurality of machines, and configuring an InfiniBand network card for each machine;
s2: setting each machine to have the same timeline information, so that the timeline data structures of all the machines are synchronous;
s3: decoding and editing an input video file to obtain decoded video data, then dividing the decoded video data into a plurality of regions according to space, rendering the decoded video data of each region in parallel, and finally obtaining a rendering result of each region;
s4: and (5) stitching the rendering results of the regions, splicing the rendering results into a complete picture, and finishing editing.
Further, the plurality of machines forming the InfiniBand network cluster in S1 includes: the system comprises a front-end machine, a plurality of decoding machines and a plurality of rendering machines.
Further, in S1, a 100Gbps InfiniBand switch is used to implement data transmission of multiple machines.
Further, in S2, the timeline information of each machine is abstracted into a timeline data structure by using a nonlinear editing system, and the timeline data structures of all the machines are synchronized by performing serialization and deserialization on the timeline data structures.
Further, in S3, the video file is input, the front-end machine is used to receive a UI operation of the user, the UI operation is converted into a data structure and an operation command of the nonlinear editing system, the back-end decoding machine and the rendering machine are driven to operate, and the front-end machine performs spatial division of the decoded video data.
Further, in S3, each decoding machine is driven by the front-end machine to receive the operation command, decode and edit the input video file to obtain decoded video data, and send the decoded video data to the corresponding rendering machine according to the space division of the front-end machine, where the number of video files decoded by each decoding machine is determined according to the video format and the format complexity of the video file.
Further, in S3, each rendering machine receives the decoded video data in the corresponding region according to a preset corresponding relationship, and the decoded video data is uplinked to the GPU for fusion and superimposition of video frames and rendering of various special effects, so as to obtain a rendering result, and then the rendering result is downlinked to the memory and is sent to the front-end machine.
Further, in S4, the front-end processor receives the rendering results of each region, stitches the rendering results according to the size and position of the space division, and splices the rendering results into a complete picture for display.
The invention has the following beneficial effects:
1. the invention adopts the InfiniBand network commonly used in the super computing architecture, the core technology of the InfiniBand network is RDMA (remote Direct Memory Access), the time delay can be greatly shortened, the bandwidth can be improved, a 100Gbps InfiniBand switch is used, one or two InfiniBand network cards are inserted into each machine, the in-out bandwidth of each machine can reach 100Gbps or 200Gbps, and the low-time-delay transmission of 8K large-format baseband data can be met.
2. Each machine of the present invention has the same timeline information, and the timeline data structures of all machines are synchronized such that all data changes involved on the timeline are synchronized, such as: the method comprises the steps of cutting \ moving \ Trim \ deleting materials, adding \ deleting \ modifying special effects, adding \ deleting subtitles, adding \ deleting tracks and the like, so that all machines in a cluster have the same timeline information and can work cooperatively correctly.
3. The invention uses a plurality of machines to form a cluster, divides the calculation tasks with heavy multilayer large-format editing into different machines for processing in a frame segmentation mode, and then uses a very high-speed network technology to realize data transmission, so that a user can realize free and smooth multilayer 8K large-format real-time editing, the operation feeling and 4K editing have no great difference, and the invention has very flexible architecture and easy expansion, and further can realize free editing with unlimited breadth, unlimited number of layers and unlimited frame rate.
Drawings
FIG. 1 is a schematic process flow diagram of an embodiment of the present invention.
FIG. 2 is a schematic diagram of a cluster architecture according to an embodiment of the present invention.
Detailed Description
For a better understanding of the present invention by those skilled in the art, the present invention will be described in further detail below with reference to the accompanying drawings and the following examples.
Example 1
As shown in fig. 1, this embodiment provides a method for implementing large-format multi-layer real-time editing based on intra-frame segmentation clustering, which includes the following steps:
s1: a traditional network networking method, such as ethernet, no matter 10GE, 25GE, 40GE, cannot meet the transmission requirement of 8K data, so this embodiment employs an InfiniBand network, the core technology of which is rdma (remote Direct Memory access), which can greatly shorten the delay and increase the bandwidth, in this embodiment, multiple machines are used to form an InfiniBand network cluster, a 100Gbps InfiniBand switch is used to implement data transmission of multiple machines, and each machine is configured with one or two InfiniBand cards, so the access bandwidth of each machine can reach 100Gbps or 200Gbps, which can meet the low-delay transmission of large-format 8K baseband data, where the multiple machines forming the InfiniBand network cluster include: the system comprises a front-end machine, a plurality of decoding machines and a plurality of rendering machines;
s2: setting each machine to have the same timeline information allows the timeline data structures of all machines to be synchronized so that all data changes involved in the timeline are synchronized, such as: shearing \ moving \ Trim \ deleting material, adding \ deleting \ modifying special effects, adding \ deleting subtitles, adding \ deleting tracks and the like, so that all machines in the cluster have the same time line information and can work cooperatively correctly;
in particular, the time line information of each machine is abstracted into a time line data structure by utilizing a nonlinear editing system, when the front-end machine operates, any change of the timeline information is reflected as the change of the data in the timeline data structure, the front-end machine sequences the timeline data structure to form binary data, by the Direct Write approach of RDMA, the front-end machine sends binary data to the memory registered by the decoding machine or the rendering machine, because the data amount of the timeline data is small compared to 4K, 8K video data, therefore, the time delay is very low and is less than 1ms, then the back-end machine receives the binary data and carries out deserialization to the binary data to form a timeline data structure consistent with the content of the front-end machine, thereby realizing the synchronization of the timeline data structures of all the machines, when the decoding machine or the rendering machine operates, the timeline data structures of other machines can be synchronized in the same way;
s3: decoding and editing an input video file to obtain decoded video data, then dividing the decoded video data into a plurality of regions according to space, rendering the decoded video data of each region in parallel, and finally obtaining a rendering result of each region, for example, for an 8K format, a typical dividing manner is to divide the decoded video data into 4 regions, and render the decoded video data of the 4 regions in parallel corresponding to an upper left region, an upper right region, a lower left region and a lower right region, and finally obtaining a rendering result of each region, specifically:
inputting a video file, receiving UI operation of a user by using a front-end machine, converting the UI operation into a data structure and an operation command of a nonlinear editing system, informing a rear-end decoding machine and a rendering machine to be synchronous, driving the rear-end decoding machine and the rendering machine to work, and carrying out space division on decoded video data by the front-end machine according to factors such as the breadth size of a timeline, the complexity of the timeline, the capacity of the machine and the like;
each decoding machine is driven by a front-end machine, receives a decoding command, decodes and edits an input video file to obtain decoded video data, sets up according to timeline information and clusters after decoding, and then performs scaling or cutting if necessary, and finally transmits the processed decoded video data to a corresponding rendering machine through an InfiniBand network according to space division of the front-end machine, wherein the number of the video files decoded by each decoding machine is determined according to the video breadth and the format complexity of the video files;
each rendering machine receives the decoded video data of the corresponding area according to a preset corresponding relation, the decoded video data are uplinked to a GPU for fusion and superposition of multilayer video pictures and graphics rendering and other operations on various special effects such as subtitles and special effects appearing in the area, rendering results are obtained, then the rendering results are downlinked to a memory and are sent to a front-end machine through an InfiniBand network;
s4: stitching the rendering results of the regions, splicing the rendering results into a complete picture, and finishing editing, wherein the stitching method specifically comprises the following steps:
and the front-end machine receives the rendering results of each area, stitches the rendering results according to the size and the position during space division, splices the rendering results into a complete picture, finally outputs the complete picture to a monitor through the board card, and simultaneously displays the non-coded MV picture on the display.
In this embodiment, a plurality of machines are used to form a cluster, a front-end machine is used to perform intra-frame segmentation to decode video data, the calculation task of heavy multilayer large-format editing is divided into different machines for processing, and then a very high-speed network technology is used to realize data transmission, so that a user can realize free and smooth multilayer large-format real-time editing, the operation feeling and 4K editing have no great difference, and as shown in fig. 2, the architecture of this embodiment is very flexible and easy to expand, and further, free editing with unlimited breadth, number of layers and frame rate can be realized.
The above description is only a preferred embodiment of the present invention, and not intended to limit the present invention, the scope of the present invention is defined by the appended claims, and all structural changes that can be made by using the contents of the description and the drawings of the present invention are intended to be embraced therein.
Claims (7)
1. The method for realizing large-format multilayer real-time editing based on intra-frame segmentation clustering is characterized by comprising the following steps of:
s1: forming an InfiniBand network cluster by using a plurality of machines, and configuring an InfiniBand network card for each machine;
s2: setting each machine to have the same timeline information, so that the timeline data structures of all the machines are synchronous;
s3: decoding and editing an input video file to obtain decoded video data, then dividing the decoded video data into a plurality of regions according to space, rendering the decoded video data of each region in parallel, and finally obtaining a rendering result of each region;
s4: stitching the rendering results of the regions, splicing the rendering results into a complete picture, and finishing editing;
in S2, the timeline information of each machine is abstracted into a timeline data structure by using the nonlinear editing system, the front-end machine sends binary data to a memory registered in the decoding machine or the rendering machine by serializing and deserializing the timeline data structure, and the back-end machine receives the binary data and deserializes the binary data to form a timeline data structure consistent with the content of the front-end machine, thereby synchronizing the timeline data structures of all machines.
2. The method for realizing large-format multi-layer real-time editing based on intra-frame segmentation clustering as claimed in claim 1, wherein the plurality of machines forming the InfiniBand network cluster in S1 comprise: the system comprises a front-end machine, a plurality of decoding machines and a plurality of rendering machines.
3. The method for realizing large-format multi-layer real-time editing based on intra-frame segmentation clustering as claimed in claim 1, wherein a 100gbps infiniband switch is utilized in S1 to realize data transmission of multiple machines.
4. The method according to claim 2, wherein the video file is input in S3, the front-end machine receives a UI operation from a user, converts the UI operation into a data structure and an operation command of a nonlinear editing system, drives a back-end decoding machine and a rendering machine to work, and performs spatial division of decoded video data by the front-end machine.
5. The method according to claim 4, wherein in step S3, each decoding machine is driven by a front-end machine, receives an operation command, decodes and edits the input video file to obtain decoded video data, and sends the decoded video data to a corresponding rendering machine according to the spatial partition of the front-end machine, and the number of video files decoded by each decoding machine is determined according to the video format and the format complexity of the video file.
6. The method according to claim 2, wherein in S3, each rendering machine receives decoded video data in a corresponding region according to a preset correspondence, and sends the decoded video data to the GPU for fusion and superimposition of video frames and rendering of various special effects to obtain a rendering result, and then sends the rendering result to the memory and to the front-end machine.
7. The method according to claim 2, wherein in S4, the front-end processor receives rendering results of each region, stitches the rendering results according to the size and position of the space division, and splices the rendering results into a complete picture for display.
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